class_docstr: Synaptic Intelligence plugin.
  
  This is the Synaptic Intelligence PyTorch implementation of the
  algorithm described in the paper
  "Continuous Learning in Single-Incremental-Task Scenarios"
  (https://arxiv.org/abs/1806.08568)
  
  The original implementation has been proposed in the paper
  "Continual Learning Through Synaptic Intelligence"
  (https://arxiv.org/abs/1703.04200).
  
  This plugin can be attached to existing strategies to achieve a
  regularization effect.
  
  This plugin will require the strategy `loss` field to be set before the
  `before_backward` callback is invoked. The loss Tensor will be updated to
  achieve the S.I. regularization effect.
docstr: Explodes a list of excluded parameters by adding a generic final ".*"
  wildcard at its end.
  
  :param excluded: The original set of excluded parameters.
  
  :return: The set of excluded parameters in which ".*" patterns have been
      added.
docstr_tok: ["Explodes","a","list","of","excluded","parameters","by","adding","a","generic","final","``",".","*","''","wildcard","at","its","end",".",":","param","excluded",":","The","original","set","of","excluded","parameters",".",":","return",":","The","set","of","excluded","parameters","in","which","``",".","*","''","patterns","have","been","added","."]
code: def explode_excluded_parameters(excluded: Set[str]) -> Set[str]:
      """
      Explodes a list of excluded parameters by adding a generic final ".*"
      wildcard at its end.
  
      :param excluded: The original set of excluded parameters.
  
      :return: The set of excluded parameters in which ".*" patterns have been
          added.
      """
      result = set()
      for x in excluded:
          result.add(x)
          if not x.endswith("*"):
              result.add(x + ".*")
      return result
  
imports: from fnmatch import fnmatch
  from typing import Optional, Sequence, Any, Set, List, Tuple, Dict, Union, TYPE_CHECKING
  import numpy
  import torch
  from torch import Tensor
  from torch.nn import Module
  from torch.nn.modules.batchnorm import _NormBase
  from .ewc import EwcDataType, ParamDict
  from avalanche.training.plugins.strategy_plugin import SupervisedPlugin
  from avalanche.training.utils import get_layers_and_params, ParamData
label_desc: Use image node_id 16 for calling the SynapticIntelligencePlugin obj's underlying member method code with example usage: obj.explode_excluded_parameters(excluded) and returns: result